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Pipl is an AI company that helps global enterprises make better fraud decisions. We're built on more than 20 years of identity data and Elephant, the industry's only large risk model trained on payment fraud.
Pipl's three products give enterprise teams modular access to the intelligence they need across payment and transaction ecosystems, where the cost of getting it wrong is highest.
Pipl Trust brings AI-native risk decisioning into payment workflows, with Elephant resolving identity across behavioral, device, and network signals in real time. Pipl Search connects identity intelligence for investigations and background checks, drawing on our global identity graph. Pipl Elements delivers phone and email signals that strengthen existing fraud models and verification workflows.
Our identity graph covers more than 5 billion identities and 740 billion signals. The world's largest payment networks, ecommerce marketplaces, and digital wallet platforms trust Pipl to get it right.
We're looking for a Product Manager with strong fraud expertise to help shape the next generation of Pipl's Trust products.
This role sits at the intersection of product, fraud intelligence, customer discovery and data science. You will develop a deep understanding of emerging fraud patterns, analyze customer and POC data to understand where fraud occurs and where our products succeed or fall short, and translate those insights into new signals, capabilities and solutions.
You will work directly with customers, Sales and Solutions teams to understand how organizations detect and mitigate fraud today, identify unmet needs, and discover new opportunities for Pipl. You will also maintain an adversarial view of our products — thinking like a fraudster to identify where our signals and models can be bypassed and what we need to do about it.
This is a hands-on product role. Success means becoming a fraud domain expert within Product and using that expertise to drive our roadmap, improve customer outcomes, and help shape Pipl's perspective on emerging fraud trends.
Continuously research emerging fraud methods, attack patterns and industry trends, and translate them into product opportunities.
Analyze labeled customer and POC data to identify fraud patterns, false positives and false negatives, understand why decisions were wrong, and identify data, signal or model gaps.
Work directly with customers, Sales and Solutions teams to understand fraud challenges, existing workflows and unmet needs.
Identify patterns across customers and turn individual problems into scalable product capabilities.
Find gaps and build better solutions
Maintain an adversarial view of Pipl's Trust products: understand how fraudsters could bypass existing signals and identify what we would miss.
Define new signals, insights and product capabilities that help customers better detect, investigate and mitigate fraud.
Turn discoveries into prioritized product requirements and drive them from concept through development, release and measurement.
Partner closely with Data Science to evaluate new features and signals and measure their impact on fraud detection and false positives.
Expand our fraud intelligence
Identify and evaluate new sources of fraud and adversarial data, including breach data, blacklists, compromised identifiers, scam intelligence and threat-intelligence providers.
Run provider evaluations with Data Science to understand coverage, quality and incremental value relative to Pipl's existing capabilities.
Work within Pipl's privacy, compliance and security requirements when evaluating new data sources.
Build Pipl's fraud expertise
Use analysis across customer data and the broader fraud landscape to develop insights into how fraud is evolving.
Partner with Marketing to translate meaningful findings into research, blogs, publications and other thought-leadership content.
Help customer-facing teams communicate Pipl's fraud capabilities and provide a strong product perspective during strategic customer discussions.
Requirements
3+ years of experience in fraud, risk, trust & safety, identity, payments or security. (Product management experience is a strong plus, not a requirement).
Hands-on fraud investigation or analytics experience — you have personally analyzed fraudulent transactions and worked to understand how they succeeded.
Strong analytical skills, including SQL and experience working with large, imperfect customer datasets.
Experience conducting customer discovery and translating customer problems into scalable product solutions.
Experience with ML-based products and working closely with Data Science teams.
Strong understanding of the fraud ecosystem and curiosity about how fraud and attacker behavior are evolving.
Ability to move comfortably between detailed data analysis, customer conversations and broader product strategy.
Excellent written, verbal and presentation skills, with the ability to communicate fraud insights to technical, customer and industry audiences.
Proven ability to take product initiatives from discovery and requirements through execution and measurement.
Nice to have: Experience with payments/e-commerce fraud, synthetic identities, mule accounts, first-party fraud, ATO or scams; familiarity with threat intelligence or breach data; experience with device intelligence, bot detection or identity resolution.